Optimal measurement placement for security constrained state estimation using hybrid genetic algorithm and simulated annealing

Abstract

This paper proposes a hybrid genetic algorithm and simulated annealing (HGS) for solving optimal measurement placement for power system state estimation. Even though the minimum number of measurement pairs is N considering the single measurement loss, their positions are required to make the system observable. HGS algorithm is a genetic algorithm (GA) using the acceptance criterion of simulated annealing (SA) for chromosome selection. The Pδ observable concept is used to check the network observability with and without single measurement pair loss contingency and single branch outage. Test results of 10-bus, IEEE 14, 30, 57, and 118-bus systems indicate that HGS is superior to tabu search (TS), GA, and SA in terms of higher frequency of the best hit and faster computational time. Copyright © 2007 John Wiley & Sons, Ltd.